Efficient computation of variable predictiveness

Abstract

Embodiments of the present invention relate to efficiently computing variable predictiveness such that an indication of variable predictiveness can be provided in real time. In this regard, aspects of the present invention enable a user (e.g., digital marketer) to input a query and, in response, receive an indication of variable predictiveness. To efficiently compute variable predictiveness in response to a submitted user query, mutual information is computed offline and, thereafter, used to generate, in real time, conditional mutual information of variables for a specified date range. The concept of conditional mutual information can be utilized to represent variable predictiveness or otherwise indication variable predictiveness, such as to identify a set of variables that accurately predict a metric. Using such an approach effectively reduces a number of data access attempts and calculations performed in real time thereby reducing utilization of a processor(s).